Scalable stochastic modelling for resilience

Bradley, Jeremy T., Cloth, Lucia, Hayden, Richard A., Kloul, Leïla, Reinecke, Philipp ORCID: https://orcid.org/0000-0002-2411-0891, Siegle, Markus, Thomas, Nigel and Wolter, Katinka 2012. Scalable stochastic modelling for resilience. Wolter, K, Avritzer, A, Vieira, M and van Moorsel, A, eds. Resilience Assessment and Evaluation of Computing Systems, Berlin. Heidelburg: Springer, pp. 115-149. (10.1007/978-3-642-29032-9_6)

Full text not available from this repository.

Abstract

This chapter summarises techniques that are suitable for performance and resilience modelling and analysis of massive stochastic systems. We will introduce scalable techniques that can be applied to models constructed using DTMCs and CTMCs as well as compositional formalisms such as stochastic automata networks, stochastic process algebras and queueing networks. We will briefly show how techniques such as mean value analysis, mean-field analysis, symbolic data structures and fluid analysis can be used to analyse massive models specifically for resilience in networks, communication and computer architectures.

Item Type:	Book Section
Date Type:	Published Online
Status:	Published
Schools:	Schools > Computer Science & Informatics
Publisher:	Springer
ISBN:	978-3-642-29031-2
Last Modified:	26 Oct 2022 07:13
URI:	https://orca.cardiff.ac.uk/id/eprint/124319

Actions (repository staff only)

Edit Item